Business Process Management systems are used to organize and manage large amounts of information.
Business process management (BPM) is focused on aligning organizations with the needs of clients. With advanced workflow technology, BPM performs an omni-directional management on enterprises from the aspect of business process, and supports enduring improvements of business process. It provides a unified modeling, executing, and monitoring environment for various businesses within an enterprise and among enterprises. BPM technology allows reduction of the mismatch between business requirements and IT systems, improvement of productivity and reduction of operating and development costs.
A business process is a collection of related, structured activities that produce a service or product that meet certain requirements. Business processes are critical to a business organization as they generate revenue and often represent a significant proportion of costs.
Business Process Management encompasses a set of methods, techniques, and tools for modeling, developing, executing, and managing business processes of an organization. BPM allows business analysts create a business process model, which is then refined by IT engineers to an executable model. The executable process model is deployed to a process engine, which executes the process by delegating tasks to resources (humans and services).
Business process performance in BPM systems is measured based on key performance indicators (KPIs). Key Performance Indicators (KPIs) are generally defined by BPM designers.
BPM designers focus on optimizing BPM models with regard to KPIs, by tuning a certain number of control parameters.
Business Process Management systems rely on an initial modeling phase where a business analyst function is determined to describe the steps, rules, and KPIs for the business process, and estimate expected performance via discrete event simulation.
Current solutions for enhancing performance of BPM systems provide information on KPI achievement. However, when KPIs need to be optimized, it is generally required to determine which control parameters need later adjustment by business analysts. However, KPIs often depend on several metrics so that it is difficult to identify the causes of sub-optimality.
Similarly, BPM (Business Process Management) modelers involved in the initial modeling phase may need to see the impact of changing some values of control parameters. Currently, those parameter changes are performed manually and the effect of these changes is experimented by launching a discrete event simulation model returning the desired KPIs.
However, this process can be very long and requires BPM experts' inputs. Some existing BPM tools are provided with a local search mechanism that speeds up tuning the control parameter vector. However, the local search engine has no knowledge about the structure of the BPM network: to tune the control parameters, this local search solution simply gets key performance indicators results from simulation, but ignores the structure of the problem, which makes it quite slow.
Accordingly, there is a need for an improved method and system for determining optimal control parameters values with regard to KPIs.